Sustainability,
Год журнала:
2024,
Номер
16(16), С. 7025 - 7025
Опубликована: Авг. 16, 2024
Land
use/land
cover
change
has
a
significant
indicative
effect
on
the
carbon
storage
of
terrestrial
ecosystems.
We
selected
Chang-Zhu-Tan
urban
agglomeration
as
research
object,
coupled
FLUS
and
InVEST
models
to
explore
changes
in
land
use
region
from
2010
2020,
predicted
their
spatiotemporal
evolution
characteristics
under
three
scenarios
2035:
natural
development
(S1),
ecological
priority
(S2)
(S3).
Spatial
autocorrelation
was
used
analyze
spatial
distribution
storage.
The
results
revealed
rapid
expansion
encroaching
cultivated
forest
resulting
total
area
1957.50
km2
by
2020.
Carbon
experienced
loss
6.86
×
106
t,
primarily
between
2015.
model
indicated
pattern
“low
middle
high
around”,
with
areas
low
showing
large-scale
faceted
aggregate
2035.
Under
different
regional
scenarios,
S3
exhibited
highest
loss,
reaching
150.93
t.
S1
decline
136.30
while
S2
only
reduction
24.26
primary
driving
factor
is
conversion
into
areas.
It
recommended
that
implementation
protection
policies
optimization
structures
effectively
minimize
ISPRS International Journal of Geo-Information,
Год журнала:
2025,
Номер
14(1), С. 30 - 30
Опубликована: Янв. 14, 2025
Riverine
coastal
megacities,
particularly
in
semi-arid
South
Asian
regions,
face
escalating
environmental
challenges
due
to
rapid
urbanization
and
climate
change.
While
previous
studies
have
examined
urban
growth
patterns
or
impacts
independently,
there
remains
a
critical
gap
understanding
the
integrated
of
land
use/land
cover
(LULC)
changes
on
both
ecosystem
vulnerability
sustainable
development
achievements.
This
study
addresses
this
through
an
innovative
integration
multitemporal
Landsat
imagery
(5,
7,
8),
SRTM-DEM,
historical
use
maps,
population
data
using
MOLUSCE
plugin
with
cellular
automata–artificial
neural
networks
(CA-ANN)
modelling
monitor
LULC
over
three
decades
(1990–2020)
project
future
for
2025,
2030,
2035,
supporting
Sustainable
Development
Goals
(SDGs)
Karachi,
southern
Pakistan,
one
world’s
most
populous
megacities.
The
framework
integrates
analysis
SDG
metrics,
achieving
overall
accuracy
greater
than
97%,
user
producer
accuracies
above
77%
Kappa
coefficient
approaching
1,
demonstrating
high
level
agreement.
Results
revealed
significant
expansion
from
13.4%
23.7%
total
area
between
1990
2020,
concurrent
reductions
vegetation
cover,
water
bodies,
wetlands.
Erosion
along
riverbank
has
caused
Malir
River’s
decrease
17.19
5.07
km2
by
highlighting
key
factor
contributing
flooding
during
monsoon
season.
Flood
risk
projections
indicate
that
urbanized
areas
will
be
affected,
66.65%
potentially
inundated
2035.
study’s
contribution
lies
quantifying
achievements,
showing
varied
progress:
26%
9
(Industry,
Innovation,
Infrastructure),
18%
11
(Sustainable
Cities
Communities),
13%
13
(Climate
Action),
16%
8
(Decent
Work
Economic
Growth).
However,
declining
bodies
pose
15
(Life
Land)
6
(Clean
Water
Sanitation),
11%,
respectively.
approach
provides
valuable
insights
planners,
offering
novel
adaptive
planning
strategies
advancing
practices
similar
stressed
megacity
regions.
Journal of Innovation & Knowledge,
Год журнала:
2024,
Номер
9(2), С. 100484 - 100484
Опубликована: Март 29, 2024
To
address
global
climate
change
and
achieve
high-quality
development,
China
has
to
reach
carbon
peaking
neutrality
targets
as
objective
requirements.
Based
on
data
from
30
Chinese
provinces
2011
2021,
this
study
used
a
two-factor
fixed
effects
mechanism
model
test
the
mechanisms
of
digital
finance
performance.
The
findings
imply
that
development
nonlinear
effect
"first
inhibit,
then
promote"
principle
Meanwhile,
both
coverage
breadth
usage
depth
have
more
significant
impact
Digital
financing
can
improve
regional
performance
through
green
technology
innovation,
industrial
upgrades,
energy
structure
optimization.
In
addition,
exhibited
heterogeneity.
Specifically,
higher
level
marketization
lower
urban–rural
income
gap,
effect.
eastern
region
advantage
being
rich
in
resources
technology,
is
obvious
compared
central
western
regions.
Therefore,
should
accelerate
integration
financial
services
with
modern
technologies
low-carbon
based
local
conditions.
Land,
Год журнала:
2025,
Номер
14(1), С. 151 - 151
Опубликована: Янв. 13, 2025
Analyzing
the
current
trends
and
causes
of
carbon
storage
changes
accurately
predicting
future
land
use
under
different
climate
scenarios
is
crucial
for
regional
decision-making
management.
This
study
focuses
on
Beijing
as
its
area
introduces
a
framework
that
combines
Markov
model,
Patch-based
Land
Use
Simulation
(PLUS)
Integrated
Valuation
Ecosystem
Services
Tradeoffs
(InVEST)
model
to
assess
at
sub-district
level.
allows
systematic
analysis
spatiotemporal
evolution
in
from
2000
2020,
including
influence
driving
factors
storage.
Moreover,
it
enables
simulation
prediction
2025
2040
various
scenarios.
The
results
show
following:
(1)
From
overall
change
showed
trend
“Significant
decrease
cropland
area;
Forest
increase
gradually;
Shrub
grassland
first
then
decrease;
Decrease
water;
Impervious
expands
large
scale”.
(2)
“decrease-increase”
fluctuation,
with
an
1.3
Tg.
In
prediction,
ecological
protection
scenario
will
contribute
achieving
goals
peak
neutrality.
(3)
Among
factors,
slope
has
strongest
impact
Beijing,
followed
by
Human
Activity
Intensity
(HAI)
Nighttime
Light
Data
(NTL).
built-up
areas,
was
found
HAI
DEM
(Digital
Elevation
Model)
have
effect,
NTL
Fractional
Vegetation
Cover
(FVC).
findings
this
offer
valuable
insights
sustainable
advancement
conservation
urban
development
Beijing.
